NVIDIA NCP-AII Questions & Answers

The related but distinct situation is “A rack reports repeated fan alerts from one slot, but operators replace another fan with the same visible color label”. The decisive evidence is that After targeted fan replacement, the specific BMC alarm clears and inlet/cooling behavior stabilizes. For the stated problem, “A known-good transceiver and link test restore the port without unnecessary adapter replacement” addresses the central condition.

The proposed validation does not isolate the reported fault. An effective closure test requires evidence that A known-good transceiver and link test restore the port without unnecessary adapter replacement.

This is weaker evidence because A one-port symptom may be caused by replaceable media rather than the network card's common hardware. The independent test must show that A known-good transceiver and link test restore the port without unnecessary adapter replacement.

The related but distinct situation is “A ClusterKit report shows two hosts consistently below the rack median in GPU-to-network performance”. A completed remediation must demonstrate that After repair the affected nodes fall within approved cluster performance variance. The deciding requirement here is “A controlled retest correlates workload occupancy, NIC counters and fabric throughput to explain the variance”.

This option serves the scenario “An operator averages all ClusterKit results into one green score even though one test suite failed every storage path in a rack”. The decisive evidence is that The final readiness report shows independent passes for compute, network and storage checks. This question instead requires “A controlled retest correlates workload occupancy, NIC counters and fabric throughput to explain the variance”.

This is weaker evidence because Cluster validation must distinguish persistent hardware defects from external contention during measurement. The independent test must show that A controlled retest correlates workload occupancy, NIC counters and fabric throughput to explain the variance.

This alternative addresses the separate case “A technician replaces a GPU successfully but does not reapply the workload partition profile required for the tenant scheduler”. The appropriate intervention is Restore and validate the approved MIG or allocation configuration after the hardware replacement. The deciding requirement here is “Update documented adapter identity, firmware, fabric mapping and host/cluster configuration after replacement”.

The suggested action targets another problem where Mechanical fit does not imply the module supports the electrical envelope of a high-power GPU chassis. It does not directly address this case, which needs Update documented adapter identity, firmware, fabric mapping and host/cluster configuration after replacement.

The related but distinct situation is “A failed GPU in a hot-running server is removed while the node remains scheduled for production jobs”. The direct fix is Drain and power down the affected node and follow qualified chassis and ESD service instructions. For the stated problem, “Update documented adapter identity, firmware, fabric mapping and host/cluster configuration after replacement” addresses the central condition.

This alternative addresses the separate case “A backup head node has no configured remote power-fencing capability, but the team expects automatic recovery from any loss of heartbeat”. The controlling explanation is that Safe automatic HA normally requires a way to ensure the former active node cannot continue writing shared resources. For the stated problem, “Loss of a heartbeat by itself does not prove the active head is safely stopped or no longer accessing shared storage” addresses the central condition.

The option would apply to “A Base Command Manager cluster relies on one head node and loses both DHCP provisioning and Slurm scheduling whenever that node powers off”. The operational evidence follows from the mechanism that BCM head-node services can be replicated to a passive peer but require compatible management, storage and failover configuration. The present scenario is distinguished by “Loss of a heartbeat by itself does not prove the active head is safely stopped or no longer accessing shared storage”.

The proposed explanation misses the decisive dependency: Loss of a heartbeat by itself does not prove the active head is safely stopped or no longer accessing shared storage. Validation would demonstrate that The failover test produces consistent quorum decisions, known active ownership and no simultaneous shared-volume mounts.

The option would apply to “A GPU cluster uses the same unsegmented VLAN for BMC administration and high-volume RoCE traffic across the leaf-spine fabric”. A completed remediation must demonstrate that A saturated data-fabric test leaves authenticated BMC access reachable and restricts unauthorized management flows. This question instead requires “A parallel checkpoint-and-training test maintains target throughput and bounded collective tail latency”.

The related but distinct situation is “A planner advertises active-active resilience for dual-rail InfiniBand but connects both rails through one upstream power circuit”. A completed remediation must demonstrate that A planned power-feed failure leaves one validated fabric rail carrying its intended training traffic. For the stated problem, “A parallel checkpoint-and-training test maintains target throughput and bounded collective tail latency” addresses the central condition.

The proposed validation does not isolate the reported fault. An effective closure test requires evidence that A parallel checkpoint-and-training test maintains target throughput and bounded collective tail latency.

This option addresses an alternative scenario (BlueField-3 adapters pass host Ethernet traffic but the embedded Arm software revision differs from the approved fabric interoperability matrix); the reported issue instead calls for Verify the selected boot image and actual running firmware version rather than trusting the flash utility exit status.

This response is applicable to a different failure: A rack of BlueField DPUs displays the expected physical links but several cards report repeated hardware health events from their embedded controller. Here the central dependency is that Firmware staging and activation can be separate steps on devices with multiple firmware images, so the specific response is Verify the selected boot image and actual running firmware version rather than trusting the flash utility exit status.

The option would apply to “A network team enables a BlueField security mode that restricts host-side reads, then declares the card defective when a host monitoring tool loses access”. The direct fix is Validate DPU management visibility through the permitted trusted path and expected restrictions. The present scenario is distinguished by “Verify the selected boot image and actual running firmware version rather than trusting the flash utility exit status”.

That change may help in a different context, but it would not establish that A concurrent workload test shows distinct assigned MIG identifiers and authorized resource visibility. The relevant response is Use stable device discovery and enforce exclusive per-instance assignment in the workload scheduler.

This response is applicable to a different failure: An administrator enables MIG mode on a supported GPU but creates no GPU or compute instances and the workload sees no device. Here the central dependency is that Logical isolation is ineffective if scheduling incorrectly shares the same device instance across untrusted jobs, so the specific response is Use stable device discovery and enforce exclusive per-instance assignment in the workload scheduler.

That change may help in a different context, but it would not establish that A concurrent workload test shows distinct assigned MIG identifiers and authorized resource visibility. The relevant response is Use stable device discovery and enforce exclusive per-instance assignment in the workload scheduler.

This alternative addresses the separate case “Two tenants see the same MIG device assignment because an orchestration template reuses one accelerator identifier”. The appropriate intervention is Use stable device discovery and enforce exclusive per-instance assignment in the workload scheduler. For the stated problem, “Persist desired MIG geometry through supported startup automation and refresh scheduler device inventory” addresses the central condition.

The suggested action targets another problem where MIG mode enablement alone does not create addressable GPU compute resources for applications. It does not directly address this case, which needs Persist desired MIG geometry through supported startup automation and refresh scheduler device inventory.

That change may help in a different context, but it would not establish that A controlled reboot restores the intended GPU and compute instances before accepting tenant jobs. The relevant response is Persist desired MIG geometry through supported startup automation and refresh scheduler device inventory.

The related but distinct situation is “Two otherwise identical optical links use transceiver firmware revisions that negotiate different advertised capabilities on the same switch”. The decisive evidence is that Readback confirms the supported optic firmware and the expected lane rate on both links. For the stated problem, “The replacement module shows accepted optical margins and zero new uncorrectable traffic errors under load” addresses the central condition.

That observation does not establish operating effectiveness of Record module firmware and calibrated optical diagnostics and perform a sustained link-quality acceptance. The needed evidence is that The replacement module shows accepted optical margins and zero new uncorrectable traffic errors under load.

This alternative addresses the separate case “A fabric upgrade updates all switch operating systems but leaves pluggable optical modules with known compatibility defects”. The strongest acceptance result is that A complete version matrix and sustained traffic test show no optic-related errors across the fabric, not merely that a command executed. The deciding requirement here is “The replacement module shows accepted optical margins and zero new uncorrectable traffic errors under load”.

The related but distinct situation is “A storage optimization changes striping width for a parallel filesystem without measuring actual training and checkpoint traffic patterns”. The direct failure mode is that Overly broad striping can increase overhead and harm small-file workloads despite high sequential throughput. The deciding requirement here is “Treating a metadata bottleneck as a GPU fault can lead to ineffective hardware upgrades”.

This option serves the scenario “A training job streams datasets from a shared NFS path and repeatedly rereads the same small files over an overloaded link”. The primary exposure is that Repeated small remote reads can leave accelerators idle even when storage capacity is ample. This question instead requires “Treating a metadata bottleneck as a GPU fault can lead to ineffective hardware upgrades”.

The option would apply to “A shared storage server reaches a high benchmark throughput but training hosts still see long I/O stalls because their mount and client NIC settings differ”. The direct failure mode is that A server-only test can conceal client-side bottlenecks that waste GPU cycles. The present scenario is distinguished by “Treating a metadata bottleneck as a GPU fault can lead to ineffective hardware upgrades”.

The proposed validation does not isolate the reported fault. An effective closure test requires evidence that The restricted container runs the CUDA sample with only the intended GPU and without privileged mode.

This would be a meaningful test for another issue (A Docker workload requires only one accelerator, but the launch command passes all eight GPUs from its shared host), but not for the required outcome: The restricted container runs the CUDA sample with only the intended GPU and without privileged mode.

The related but distinct situation is “A Docker image starts on a CUDA-capable node but silently loads a CPU-only framework wheel”. A completed remediation must demonstrate that The framework reports the expected accelerator device and a measured operation uses GPU utilization. For the stated problem, “The restricted container runs the CUDA sample with only the intended GPU and without privileged mode” addresses the central condition.